-------- Ursprüngliche Nachricht -------- Von: Xenofon Fafoutis 00000134bbe013e9-dmarc-request@COMSOC-LISTSERV.IEEE.ORG Gesendet: 12. Februar 2020 16:10:42 MEZ An: tccc-announce@COMSOC.ORG Betreff: [TCCC-ANNOUNCE] IEEE ITSC 2020 - SS on Beyond Traditional Sensing for Intelligent Transportation
CALL FOR PAPERS:
ITSC 2020 - The 23rd IEEE International Conference on Intelligent Transportation Systems
September 20-23, 2020. Rhodes, Greece.
------------------------------- Special Session on *Beyond Traditional Sensing for Intelligent Transportation* ------------------------------- https://tinyurl.com/u5bz6v9 ------------------------------
Over the past few decades, sensors have not only become more advanced but also made impressive strides across an increasing number of sensing modalities. Despite the improved capabilities and breadth of available sensor systems, those used for intelligent transportation have remained relatively uniform across platforms; as a result, the algorithms and techniques being designed do not take full advantage of the rich information modern sensors can provide. Since all tasks -- including perception, localisation, decision-making, and learning -- are built on top of sensing, exploring alternative approaches to sensing is a compelling research area that can render all subsequent tasks more robust and accurate.
The objective of this special session is to explore unconventional sensing for intelligent transportation in three ways. Firstly, it will investigate sensor systems that are not typically applied to certain transportation tasks, such as radar for precise localisation, audio for failure detection, and RF sensing for road traffic estimation. Secondly, it will explore untraditional sensor configurations and placements, such as ground-facing cameras using shadows to detect occluded moving objects. Lastly, it will look into the sensing of commonly overlooked information, such as the use of atmospheric sensors for gauging road surface traction or in-vehicle sensors for driving analysis. Via these three themes, this special session aims to stimulate discussion and research into untraditional sensing in order to improve the reliability and accuracy of transportation systems.
Topics of interest include, but are not limited to: * Localisation and navigation using radars (e.g., scanning, Doppler, and ground-penetrating); * Ego-noise and soundscape modelling and interpretation (e.g., sound-based failure detection, terrain/road surface status classification, urban sound source detection and localisation); * Event-based (neuromorphic) vision for localisation and perception in challenging scenarios; * Multi-spectral imaging (e.g. IR or polarimetric cameras for localisation and perception under difficult visibility); * In-vehicle sensing and wearable computing for failure detection, driver and passenger behaviour modelling; * Far infrared sensing; * Texture odometry; * Novel sensor hardware and designs; * Unconventional sensor placements or multi-sensor systems; * Optimal sensor scheduling and control in complex and/or multi-agent / social environments; * Astronomical (skyward-facing), atmospheric or odor-based sensing; * IoT technology for intelligent transportation and Internet of Vehicles (IoV); * Passive Wireless/RF sensing.
------------------------------- *Important Dates* Paper Submission Deadline: March 02, 2020 Notification of Acceptance: May 10, 2020 Final Paper Submission Deadline: June 10, 2020 Conference Dates: September 20-23, 2020
Authors are kindly invited to notify the organisers of their submissions.
Papers submitted to this Special Session are reviewed according to the same rules as the submissions to the regular sessions of ITSC2020. Submissions to regular and special sessions follow identical format, instructions, deadlines and procedures.
Please find more info on the ITSC2020 website https://www.ieee-itsc2020.org/
------------------------------- *Organizers* Letizia Marchegiani, Aalborg University, Denmark. lm@es.aau.dk Dimitri Ognibene, University of Essex, UK. dimitri.ognibene@essex.ac.uk Daniele De Martini, University of Oxford, UK. daniele@robots.ox.ac.uk Xenofon Fafoutis, Technical University of Denmark (DTU), Denmark. xefa@dtu.dk Yan Wu, A*STAR Institute for Infocomm Research, Singapore. wuy@i2r.a-star.edu.sg Sahar Abbaspour, Volvo Car Corporation, Sweden. sahar.abbaspour@volvocars.com Matthew Gadd, University of Oxford, UK. mattgadd@robots.ox.ac.uk
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